Competing Risks and Survival Analysis

Kees van Montfort; Peter Fennema; Wendimagegn Ghidey

doi:10.1007/978-3-642-55345-5_5

Competing Risks and Survival Analysis

Kees van Montfort, Peter Fennema, Wendimagegn Ghidey

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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Abstract

The analysis of time-to-event data in the presence of competing risks is part of many studies today. However, the impact of the interrelationship between the competing risks on the interpretation of the results seems to be unclear to many researchers, however. We try to provide a guide to researchers interested in analysing competing risks data. Estimation of the cause-specific hazard function, the cumulative incidence function, the Gray test statistic, and the multi-stage models for analysing competing risks data are explained. Furthermore, we apply the theoretical methodology and illustrate the fundamental problems of interpreting the results of competing risk analyses by using empirical data in the field of outcome research in orthopaedics.

Original language	English
Title of host publication	Developments in Statistical Evaluation of Clinical Trials
Editors	Kees van Montfort, Johan Oud, Wendimagegn Ghidey
Place of Publication	Heidelberg
Publisher	Springer
Chapter	5
Pages	85-96
ISBN (Electronic)	9783642553455
ISBN (Print)	9783642553448
DOIs	https://doi.org/10.1007/978-3-642-55345-5_5
Publication status	Published - 2014
Externally published	Yes

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title = "Competing Risks and Survival Analysis",

abstract = "The analysis of time-to-event data in the presence of competing risks is part of many studies today. However, the impact of the interrelationship between the competing risks on the interpretation of the results seems to be unclear to many researchers, however. We try to provide a guide to researchers interested in analysing competing risks data. Estimation of the cause-specific hazard function, the cumulative incidence function, the Gray test statistic, and the multi-stage models for analysing competing risks data are explained. Furthermore, we apply the theoretical methodology and illustrate the fundamental problems of interpreting the results of competing risk analyses by using empirical data in the field of outcome research in orthopaedics.",

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